3rd Year Stats Exam

Questão 1 de 80

1

What is the purpose of performing a linear regression analysis?

Selecione uma das seguintes:

To identify potential outliers in the data
To fit the data to a model that defines y as a function or 2 or more variables
To determine the dependence of a dependent variable on a predictor/independent variable
To perform multiple comparisons whilst controlling overall type 1 error rate
To derive robust confidence intervals

Explicação

Questão 2 de 80

1

Which axis does the dependent variable go on?

Selecione uma das seguintes:

y
x

Explicação

Questão 3 de 80

1

What does the mean of the x and y values give you in a linear regression analysis?

Selecione uma das seguintes:

The size of the force which the points exert on the line of best fit
The leverage of those data points
The fit and slope of the model
The centre of gravity and pivot point of the data

Explicação

Questão 4 de 80

1

What does the R-squared value represent?

Selecione uma das seguintes:

How well the model fits the data (0 - 1)
The slope coefficient
The distribution of the residuals
The level of multicolinearity in the model

Explicação

Questão 5 de 80

1

What does an R-squared value of 0.068 and a slope coefficient (b1) value of 0.12 mean?

Selecione uma das seguintes:

The model can explain 68% of the data and for every unit of independent variable, the dependent variable goes up 12 units
The fit of the model to the data is 0.12% and the influence that the data points have on the model is 0.68%
The data points have an influence of 68% on the model and 12% on the outcome
The model can explain 6.8% of the data and for every unit of independent variable, the dependent variable goes up 0.12 units

Explicação

Questão 6 de 80

1

In order to identify potential outliers:

Selecione uma das seguintes:

Standardised residual >2 is worth checking, if more than 5% of the residuals >2 may indicate model is a poor fit
Standardised residual >3 is worth checking, if more than 5% of the residuals >2 may indicate that the model is a poor fit
Standardised residual >2.5 is worth checking, if more than 5% of the residuals >2 may indicate that the model is a poor fit
Standardised residual >3 is worth checking, if more than 10% of the residuals >2 may indicate that the model is a poor fit

Explicação

Questão 7 de 80

1

What does Cook's distance tell us when performing model diagnostics to see if the regression model is stable or biased by a few cases?

Selecione uma das seguintes:

influence of data point on predicted values (0 = no influence, 1 = complete influence)
standardised measures of how much each element of the model would change if data point was removed (values >1 = substantial influence)
how susceptible the mean is to being biased by the outliers present in the data
measure of overall influence of each individual data point on the overall model (>1 = concern)

Explicação

Questão 8 de 80

1

What does the Leverage value tell us when performing model diagnostics to see if the regression model is stable or biased by a few cases?

Selecione uma das seguintes:

influence of data point on predicted values (0 = no influence, 1 = complete influence)
standardised measures of how much each element of the model would change if data point was removed (values > 1 = substantial influence)
measure of overall influence of each individual data point on the overall model (> 1 = concern)
precisely how large the standardised residuals are

Explicação

Questão 9 de 80

1

With regard to model diagnostics, what do the DFFit and DFBeta values tell us about the data model?

Selecione uma das seguintes:

they are standardised measures of how much each element of the model would change if that data point was removed (values > 1 = substantial influence)
they indicate the influence of that data point on predicted values (0 = no influence, 1 = complete influence)
whether or not the standardised residuals are worth checking and if they indicate that the model is a poor fit
they summarise the equation: 2(k+1)/n where k = number of predictors and n = number of data points

Explicação

Questão 10 de 80

1

With regard to the model diagnostic called the Leverage value, what defines whether or not the data point is worth investigating?

Selecione uma das seguintes:

if >2(k+1)/n where k = number of predictors (2 for simple linear regression) and n = number of data points
if >2(k+1)/n where k = number of predictors (1 for simple linear regression) and n = number of data points
if >2(K+1)/n where k = number of data points and n = number of predictors (1 for simple linear regression)
if >n(k+1)/2 where k = number of predictors (1 for simple linear regression) and n = number of data points
if >2(n+1)/k where k = number of predictors (1 for simple linear regression) and n = number of data points

Explicação

Questão 11 de 80

1

Multiple linear regression does what?

Selecione uma das seguintes:

fits the data to a model that defines y as a function of 2 or more variables - determines the effect of an independent variable on the dependent variable taking account of other variables
provides an analysis of variance and determines if an interaction is present in the data
determines the dependence of a dependent variable on a predictor/independent variable and allows outliers to be identified from x, y plot or from standardised residual plot

Explicação

Questão 12 de 80

1

With regard to multiple linear regression, what is the correct form of the equation for the model which is fitted? (all of the numbers are technically subscript)

Selecione uma das seguintes:

y = b0 + b1x2 + b2x1
y = b0 + b1x1 + b2x2 +....
y = b0 + b1 + b2x
y = b0 + b1x1 + b2x2

Explicação

Questão 13 de 80

1

What does the F-ratio represent?

Selecione uma das seguintes:

the average variability due to the model divided by the average variability due to the residuals
the unexplained variability divided by the variability due to the model
the signal to noise ratio multiplied by the number of data points
the variance in the model divided by the R-squared value

Explicação

Questão 14 de 80

1

With regard to multiple linear regression, whenever you fit a predictor variable, that takes up...

Selecione uma das seguintes:

one slope parameter
two degrees of freedom
one degree of freedom
one R-squared value

Explicação

Questão 15 de 80

1

As colinearity increases what effect does this have?

Selecione uma das seguintes:

standard errors of b coefficients decrease therefore confidence increases
limits F-ratio value and variance inflation factor
coefficients become stable
standard errors of b coefficients increase and therefore confidence decreases

Explicação

Questão 16 de 80

1

How do you interpret the variance inflation factor (VIF) when assessing multicolinearity?

Selecione uma das seguintes:

A VIF > 5 or an avereage VIF > 2 is problematic
A VIF > 10 or an average VIF > 1 is problematic
A VIF > 2 or an average VIF > 1 is problematic
A VIF > 10 or an average VIF > 2 is problematic

Explicação

Questão 17 de 80

1

How do you interpret the tolerance factor when assessing multicolinearity?

Selecione uma das seguintes:

< 5 is problematic
< 10 is problematic
< 2 is problematic
< 0.1 is problematic
< 1 is problematic

Explicação

Questão 18 de 80

1

When does multicolinearity truly pose a problem?

Selecione uma das seguintes:

when predicting y using the multiple regression equation
when you want to look inside the model at the effect of individual predictors
when you want to perform separate correlations for each x variable
when you want to quantify the relationship between an independent and dependent variable

Explicação

Questão 19 de 80

1

How do you help solve the problem of multicolinearity?

Selecione uma das seguintes:

always take a colinear variable out
combine predictors into a single predictor (as long as it makes biological sense)
rely on automatic variable selection
remove all outliers

Explicação

Questão 20 de 80

1

With regard to hierarchical multiple regression, what value do you use when comparing new model to previous model?

Selecione uma das seguintes:

F-ratio
Cook's distance
R-squared
variance inflation factor
tolerance factor

Explicação

Questão 21 de 80

1

For multiple linear regression assumptions, what must the variables be?

Selecione uma das seguintes:

dependent variables = quantitative or categorical
predictor variable = qualitative and continuous
dependent variables = qualitative
predictor variable = continuous
dependent variables = qualitative and continuous
predictor variable = quantitative or categorical
dependent variables = continuous or categorical
predictor variable = quantitative or categorical

Explicação

Questão 22 de 80

1

When considering multiple linear regression assumptions, how do you assess the independence of the residuals?

Selecione uma das seguintes:

assess the DFFit and DFBeta values
use the Welch's test
use Gabriel's test
use the Durbin-Watson test

Explicação

Questão 23 de 80

1

For multiple linear regression, how large should the sample size be?

Selecione uma das seguintes:

10 times the number of predictors tested
5 times the number of predictors tested
at least 30
at least 40

Explicação

Questão 24 de 80

1

What would an interaction among predictors look like in the form of an equation?

Selecione uma das seguintes:

effect of height + effect of weight = overall effect on SBP
effect of height + overall effect on SBP = effect of weight
effect of height x effect of weight = overall effect on SBP

Explicação

Questão 25 de 80

1

What is simple linear regression equal to?

Selecione uma das seguintes:

paired t-test
unpaired t-test
unpaired, two-tailed t-test
paired, one-tailed t-test

Explicação

Questão 26 de 80

1

A one-way anova is the same as what?

Selecione uma das seguintes:

unpaired t-test
paired t-test
simple linear regression
multiple regression

Explicação

Questão 27 de 80

1

What does a one-way ANOVA do?

Selecione uma das seguintes:

analyses how much of the overall variance can be explained by variation between group means compared to the unexplained variation within a group
fits data to a model that defines y as a function of 2 or more variables
performs separate correlations for each x variable
determines the dependence of a dependent variable on a predictor/independent variable

Explicação

Questão 28 de 80

1

What does the total variability equal?

Selecione uma das seguintes:

total squares divided by the degrees of freedom
the F-ratio
the difference between each individual data point and the overall mean
error mean squares divided by degrees of freedom

Explicação

Questão 29 de 80

1

The F-ratio is:

Selecione uma das seguintes:

higher the larger the difference of the group means from the overall mean and smaller the amount of random variability
lower the larger the difference of the group means from the overall mean and smaller the amount of random variability
higher the larger the difference of the group means from the overall mean and larger the amount of random variability
higher the smaller the difference of the group means from the overall mean and smaller the amount of random variability

Explicação

Questão 30 de 80

1

When is the ANOVA most robust to deviations from normality and equality of variance?

Selecione uma das seguintes:

when effect size is large
when the F-ratio is high
when the degrees of freedom are greater than 10
when the group sizes are equal

Explicação

Questão 31 de 80

1

If group sizes are unequal and equality of variance is not met then which correction do you use?

Selecione uma das seguintes:

Games-Howell's
Durbin-Watson's
Gabriel's
Tukey's
Welch's

Explicação

Questão 32 de 80

1

What are post-hoc tests used for?

Selecione uma das seguintes:

performing multiple comparisons whilst controlling overall type 2 error rate
performing multiple comparisons whilst controlling overall type 1 error rate
when there is a specific hypothesis to be tested
when group size is not equal

Explicação

Questão 33 de 80

1

You use Tukey's test when which of the following is true? (multiple correct answers)

Selecione uma ou mais das seguintes:

sample sizes are unequal
sample sizes are equal
you require good trade-off between type 1 and type 2 errors
you are interested in comparing all groups vs a single control group
you wish to cut down on the number of comparisons that you make

Explicação

Questão 34 de 80

1

When would you use Bonferroni as a post-hoc test? (multiple correct answers)

Selecione uma ou mais das seguintes:

when you don't need a high level of confidence
when you aren't performing multiple comparisons
when you require a conservative test
when you need a high level of confidence
when sample sizes are equal

Explicação

Questão 35 de 80

1

When would you use Dunnet's as a post-hoc test? (multiple correct answers)

Selecione uma ou mais das seguintes:

when interested in comparing all groups versus a single control group
when sample sizes are equal
when you want to cut down comparisons
when you want a good trade-off between type 1 and type 2 errors

Explicação

Questão 36 de 80

1

Separate, unpaired t-tests to do comparisons will increase your chance of getting what?

Selecione uma das seguintes:

a false -ve
a type 2 error
a false +ve
biased data

Explicação

Questão 37 de 80

1

If you have a sample which has an n number of 10 and a sample with an n number of 12, which post hoc test should you use?

Selecione uma das seguintes:

Gabriel's
Hochberg's GT2
Games-Howell
Tukey

Explicação

Questão 38 de 80

1

If there is any doubt about equality of variance then which post-hoc test should you use?

Selecione uma das seguintes:

Gabriel's
Hochberg's GT2
Games-Howell
Sidak

Explicação

Questão 39 de 80

1

Complete this statement relating to planned contrasts:
Always _________________________ than number of groups

Selecione uma das seguintes:

ten times the number of contrasts
more contrasts
one more contrast
two times the number of contrasts
one fewer contrast

Explicação

Questão 40 de 80

1

When doing orthogonal contrasts, the contrasts are independent so you can... (multiple correct answers)

Selecione uma ou mais das seguintes:

enter weights for most of the variables
trust p-values as you aren't inflating the type 1 error rate
ignore the F-ratio value and R-squared value
not worry about doing any corrections for multiple comparisons

Explicação

Questão 41 de 80

1

"tests for trends in the data, which cannot be obtained directly using post-hoc tests, when there is a logical order to the groups entered"
To what is this statement referring to?

Selecione uma das seguintes:

Planned contrasts
Orthogonal contrasts
Polynomial contrasts

Explicação

Questão 42 de 80

1

An independent factorial ANOVA does what?

Selecione uma das seguintes:

each level of one factor is tested against at least one level of the other
performs multiple comparisons whilst controlling overall type 1 error rate
divides total variability in the data set into different sources
each level of one factor is tested at each level of the other

Explicação

Questão 43 de 80

1

Sidak is the best correction for what?

Selecione uma das seguintes:

independent ANOVA
one-way ANOVA
repeated measures ANOVA
multiple linear regression

Explicação

Questão 44 de 80

1

Standard contrasts and post hoc tests are only available to examine main effects and are therefore most useful when:

Selecione uma das seguintes:

there is no unnecessary variability in the data
there is no interaction
the sphericity assumption is met
group sizes are equal

Explicação

Questão 45 de 80

1

A p value of less than 0.5 means that....

Selecione uma das seguintes:

there is a less than 0.5% chance of committing a type 1error
there is a less than 5% chance of committing a type 2 error
there is a less than 5% chance of committing a type 1 error
there is a less than 0.5% chance of committing a type 2 error

Explicação

Questão 46 de 80

1

Standard error the proportion equals....

Selecione uma das seguintes:

Explicação

Questão 47 de 80

1

Power =

Selecione uma das seguintes:

1 - type 1 error rate
1 - type 2 error rate
1 - (type 1 + type 2 error rate)
type 2 error rate - type 1 error rate

Explicação

Questão 48 de 80

1

Power can be increased by....

Selecione uma das seguintes:

increasing effect size. decreasing random variation. decreasing sample size.
increasing effect size. increasing random variation. increasing sample size
decreasing effect size. increasing random variation. increasing sample size
increasing effect size. decreasing random variation. increasing sample size

Explicação

Questão 49 de 80

1

This gives you a standardised effect size for a difference between means, what is it called?

Selecione uma das seguintes:

Welch's correction
Cohen's d
Games-Howell test
Sidak correction
standard error of the proportion

Explicação

Questão 50 de 80

1

how do you calculate expected frequency?

Selecione uma das seguintes:

(row total + column total)/overall total
(row total - column total)/overall total
(row total x column total)/overall total

Explicação

Questão 51 de 80

1

How do you calculate degrees of freedom from a contingency table?

Selecione uma das seguintes:

df = (rows - 1) x (columns -1)
df = (rows + 1) x (columns +1)
df = (rows - 1) / (columns -1)
df = (rows x 2) + (columns x 2)

Explicação

Questão 52 de 80

1

With regard to categorical data - what must be satisfied in order for the analysis to be reliable?

Selecione uma das seguintes:

The assumption that at least 50% of expected frequency must be more than or equal to 5
Dunnet's test
The assumption that at least 80% of expected frequency must be more than or equal to 5
The same assumptions as multiple linear regression

Explicação

Questão 53 de 80

1

Which graph indicates an interaction?

Selecione uma das seguintes:

Explicação

Questão 54 de 80

1

What does simple effects analysis do? (multiple correct answers)

Selecione uma ou mais das seguintes:

probes where a certain effect is happening
performs an ANOVA to allow you to reject/accept a null hypothesis
analyses the differences between levels of one variable
performs multiple comparisons whilst controlling overall type 2 error rate

Explicação

Questão 55 de 80

1

Which multiple comparison correction should you choose after simple effects analysis in order to control the overall type 1 error rate?

Selecione uma das seguintes:

Bonferroni
LSD
Sidak

Explicação

Questão 56 de 80

1

Repeated measures ANOVA requires the data to have/be:

Selecione uma ou mais das seguintes:

independent
not independent
naturally paired
sorted into even group sizes

Explicação

Questão 57 de 80

1

What is the definition of sphericity?

Selecione uma das seguintes:

“noise” in the relationship between the independent variables and the dependent variable is the same across all values of the independent variables
equality of differences between linked values in each group
well-modeled by a normal distribution and likely for a random variable underlying the data set to be normally distributed
residuals are (roughly) normal and (approximately) independently distributed with a mean of 0 and some constant variance

Explicação

Questão 58 de 80

1

Which test provides a fix for sphericity?

Selecione uma das seguintes:

Welch's correction
Games-Howell test
Gabriel's test
Mauchy's test

Explicação

Questão 59 de 80

1

How can we adjust the degrees of freedom and change the significance level associated with the F-statistic?

Selecione uma das seguintes:

Mauchy's test
Welch's correction
Green House-Geisser correction
Gabriel's test

Explicação

Questão 60 de 80

1

Which post hoc test is most robust and most conservative for a repeated measures ANOVA?

Selecione uma das seguintes:

Sidak
Tukey
Dunnets
Bonferroni

Explicação

Questão 61 de 80

1

If parametric assumptions are in doubt, we must use the non-parametric equivalent of a single factor repeated measures ANOVA which is:

Selecione uma das seguintes:

Durbin-Watson test
Friedman test
Gabriel's test
Hochberg's GT2 test

Explicação

Questão 62 de 80

1

For which analysis do BOTH the equality of variance assumption and sphericity assumption apply?

Selecione uma ou mais das seguintes:

Non-linear regression
Two-way ANOVA
Independent ANOVA
Mixed model ANOVA
Repeated measures ANOVA

Explicação

Questão 63 de 80

1

In terms of polynomial regression, what happens if you add further terms to the polynomial? (multiple correct answers)

Selecione uma ou mais das seguintes:

the fit will automatically improve
there is a risk of over-fitting the model
the significance level associated with the F-statistic changes
the R-squared value will increase

Explicação

Questão 64 de 80

1

In terms of nonlinear regression, why would you want to try multiple starting parameters?

Selecione uma das seguintes:

to ensure that the interaction between the variables is taken into account
to ensure that the computer has found the global minimum
to ensure that the computer has found the local minimum
to ensure that an accurate scientific relationship is found

Explicação

Questão 65 de 80

1

How would you calculate the Sum of Squares (SS)?

Selecione uma das seguintes:

add all the standard deviations together and square that value
square the mean from each sample and add those together
square each standard deviation and add them all together
square each standard deviation and add this to the variance

Explicação

Questão 66 de 80

1

Variance is calculated by doing what?

Selecione uma das seguintes:

dividing the standard deviations by the degrees of freedom
dividing the sum of squares by the degrees of freedom
multiplying the degrees of freedom by the mean
multiplying the standard deviations by the sum of squares

Explicação

Questão 67 de 80

1

How do we define the normal distribution curve?

Selecione uma das seguintes:

the population mean is the height and the sum of squares is the distance from the midline of the curve to the edge
the variance is the height and the population mean is the distance from the midline of the curve to the edge
the population standard deviation is the height and the population mean is the distance from the midline of the curve to the edge
the population mean is the height and the population standard deviation is the distance from the midline of the curve to the edge

Explicação

Questão 68 de 80

1

How do you calculate a z-score?

Selecione uma das seguintes:

(x - mean) /sd
(x - sd)/mean
(mean-x)/sd
(x + mean)/sd

Explicação

Questão 69 de 80

1

Choose all of the correct statements

Selecione uma ou mais das seguintes:

approximately 99% of normally-distributed values lie between +- 2 sds from the mean
approximately 95% of normally-distributed values lie between +-2 sds from the mean
approximately 99.9% of normally-distributed values lie between +- 2.6 sds from the mean
approximately 99% of normally-distributed values lie between +- 2.6 sds from the mean
approximately 99.9% of normally-distributed values lie between +- 3 sds from the mean
approximately 95% of normally-distributed values lie between +- 3 sds from the mean

Explicação

Questão 70 de 80

1

How do you calculate SEM and therefore, confidence intervals?

Selecione uma das seguintes:

SEM = sd x square root of n and therefore a 95% CI would be +- 1.96 x SEM
SEM = sd/square root of n and therefore a 95% CI would be +- 3 x SEM
SEM = sd x square root of n and therefore a 95% CI would be +- 2.6 x SEM
SEM = sd/square root of n and therefore a 95% CI would be +- 1.96 x SEM

Explicação

Questão 71 de 80

1

Which statement is true?

Selecione uma das seguintes:

P < 0.05 means that 5% of the results arose by chance if the null hypothesis is true
P < 0.05 means <5% probability of the results arising by chance if the null hypothesis is true
P < 0.05 means <0.05% probability of the results arising by chance if the null hypothesis is true
P < 0.05 means that <0.5% probability of the results arising by chance if the null hypothesis is true

Explicação

Questão 72 de 80

1

Choose the correct statements

Selecione uma ou mais das seguintes:

type 1 error rate is conventionally set to 5% ( P < 0.05)
type 2 error rate is conventionally set to 5% ( P < 0.05)
type 1 error rate = 1 - power
type 2 error rate = 1 - power
if you accept a statistical power of 80% it will mean that you have a type 2 error rate of 20%
if you accept a statistical power of 80% it will mean that you have a type 1 error rate of 20%

Explicação

Questão 73 de 80

1

What happens if you design an experiment with 3 groups and are tempted to test for differences between the means using 3 separate t-tests? (multiple correct answers)

Selecione uma ou mais das seguintes:

you will increase the chance of making a type 2 error
you will increase the chance of making a type 1 error
you will inflate your p-value
you will decrease your p-value

Explicação

Questão 74 de 80

1

Which statements are correct regarding the Pearson Correlation Coefficient?

Selecione uma ou mais das seguintes:

+- 0.5 is a large effect
+- 0.1 is a small effect
+- 1 is a small effect
it measures how close the data points are to a straight line that best describes the linear relationship
r = +0.1 refers to a perfect straight line with a positive slope
r = -1 refers to a perfect straight line with a negative slope

Explicação

Questão 75 de 80

1

How is the line of best fit created in simple linear regression?

Selecione uma das seguintes:

by minimising the total sum of squares
by minimising the sum of squares of the residuals
by creating an equation which fits the model best
by entering the data into the computer in Hierarchical form

Explicação

Questão 76 de 80

1

How do you calculate R squared?

Selecione uma das seguintes:

1 - (SS of the residuals/total SS)
1 + (SS of the residuals/total SS)
1 - (total SS/SS of the residuals)
1 + (total SS/SS of the residuals)

Explicação

Questão 77 de 80

1

Shapiro Wilk's test is used to...

Selecione uma das seguintes:

check for sphericity
correct degrees of freedom
ascertain that residuals are random and normally distributed
minimise the sum of squares of the residuals

Explicação

Questão 78 de 80

1

When entering more than 2 categories as dummy variables... (multiple correct answers)

Selecione uma ou mais das seguintes:

the thing that you're comparing the baseline to gets a 1
the thing that you're comparing the baseline to gets a 0.1
1 fewer dummy variables than number of categories
baseline condition gets a value of 0
baseline condition gets a value of 1.5

Explicação

Questão 79 de 80

1

Bonferroni test on its own - the p-values need to be less than what to claim significance?

Selecione uma das seguintes:

0.05/number of categories
0.05/n
0.05/number of comparisons
0.05/variance

Explicação

Questão 80 de 80

1

Normally distributed variables X and Y are significantly correlated with a p level of 0.006 and a Pearson’s correlation coefficient of 0.468. Approximately how much of the variability in X and Y can be explained by this correlation?

Selecione uma das seguintes:

32%
47%
22%
13%

	Criado por Jessica Whittick mais de 7 anos atrás

University Statistics Quiz sobre 3rd Year Stats Exam, criado por Jessica Whittick em 04-01-2017.

3rd Year Stats Exam

Questão 1 de 80

What is the purpose of performing a linear regression analysis?

Selecione uma das seguintes:

Explicação

Questão 2 de 80

Which axis does the dependent variable go on?

Selecione uma das seguintes:

Explicação

Questão 3 de 80

What does the mean of the x and y values give you in a linear regression analysis?

Selecione uma das seguintes:

Explicação

Questão 4 de 80

What does the R-squared value represent?

Selecione uma das seguintes:

Explicação

Questão 5 de 80

What does an R-squared value of 0.068 and a slope coefficient (b1) value of 0.12 mean?

Selecione uma das seguintes:

Explicação

Questão 6 de 80

In order to identify potential outliers:

Selecione uma das seguintes:

Explicação

Questão 7 de 80

What does Cook's distance tell us when performing model diagnostics to see if the regression model is stable or biased by a few cases?

Selecione uma das seguintes:

Explicação

Questão 8 de 80

What does the Leverage value tell us when performing model diagnostics to see if the regression model is stable or biased by a few cases?

Selecione uma das seguintes:

Explicação

Questão 9 de 80

With regard to model diagnostics, what do the DFFit and DFBeta values tell us about the data model?

Selecione uma das seguintes:

Explicação

Questão 10 de 80

With regard to the model diagnostic called the Leverage value, what defines whether or not the data point is worth investigating?

Selecione uma das seguintes:

Explicação

Questão 11 de 80

Multiple linear regression does what?

Selecione uma das seguintes:

Explicação

Questão 12 de 80

With regard to multiple linear regression, what is the correct form of the equation for the model which is fitted? (all of the numbers are technically subscript)

Selecione uma das seguintes:

Explicação

Questão 13 de 80

What does the F-ratio represent?

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Questão 14 de 80

With regard to multiple linear regression, whenever you fit a predictor variable, that takes up...

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Questão 15 de 80

As colinearity increases what effect does this have?

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Questão 16 de 80

How do you interpret the variance inflation factor (VIF) when assessing multicolinearity?

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Questão 17 de 80

How do you interpret the tolerance factor when assessing multicolinearity?

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Questão 18 de 80

When does multicolinearity truly pose a problem?

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Questão 19 de 80

How do you help solve the problem of multicolinearity?

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Questão 20 de 80

With regard to hierarchical multiple regression, what value do you use when comparing new model to previous model?